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The second functional derivative of the effective potential of pure fermionic field theories is rewritten in a factorized form which facilitates the evaluation of the renormalisation flow rate of the effective action in the Wetterich…

High Energy Physics - Theory · Physics 2015-06-16 A. Jakovac , A. Patkos

The cutoff scheme dependence in the several formulations of the Exact Renormalization Group (ERG) is investigated. It is shown that the cutoff scheme dependence of the Wilsonian effective action is regarded as a certain coordinate…

High Energy Physics - Theory · Physics 2007-05-23 Jun-Ichi Sumi , Wataru Souma , Ken-Ichi Aoki , Haruhiko Terao , Keiichi Morikawa

Goal oriented error estimation and adaptive procedures are essential for the accurate and efficient evaluation of numerical simulations that involve complex domains. By locally improving the approximation quality we can solve expensive…

Previously proposed procedure for improving the effective potential by using renormalization group equation (RGE) is generalized so as to be applicable to any system containing several different mass scales. If one knows L-loop effective…

High Energy Physics - Phenomenology · Physics 2017-02-01 Masako Bando , Taichiro Kugo , Nobuhiro Maekawa , Hiroaki Nakano

We consider the problem of jointly estimating the parameters as well as the structure of binary valued Markov Random Fields, in contrast to earlier work that focus on one of the two problems. We formulate the problem as a maximization of…

Machine Learning · Statistics 2008-11-11 M. Kolar , E. P. Xing

We investigate finite lattice approximations to the Wilson Renormalization Group in models of unconstrained spins. We discuss first the properties of the Renormalization Group Transformation (RGT) that control the accuracy of this type of…

Statistical Mechanics · Physics 2015-06-25 A. Cacciuto , E. B. Gregory , A. Travesset

We study finite element approximations of second-order elliptic problems with measure-valued right-hand sides supported on lower-dimensional sets. The exact solution generally lacks $H^1$-regularity due to the source singularity, which…

Numerical Analysis · Mathematics 2026-03-10 Huadong Gao , Yuhui Huang

A wide variety of (fixed-point) iterative methods for the solution of nonlinear equations (in Hilbert spaces) exists. In many cases, such schemes can be interpreted as iterative local linearization methods, which, as will be shown, can be…

Numerical Analysis · Mathematics 2019-10-16 Pascal Heid , Thomas P. Wihler

Many applications using large datasets require efficient methods for minimizing a proximable convex function subject to satisfying a set of linear constraints within a specified tolerance. For this task, we present a proximal projection…

Optimization and Control · Mathematics 2024-12-10 Howard Heaton

This work presents a unified framework that combines global approximations with locally built models to handle challenging nonconvex and nonsmooth composite optimization problems, including cases involving extended real-valued functions. We…

Optimization and Control · Mathematics 2026-02-19 Welington de Oliveira , Johannes O. Royset

The critical exponent $\eta $ is not well accounted for in the Polchinski exact formulation of the renormalization group (RG). With a particular emphasis laid on the introduction of the critical exponent $\eta $, I re-establish (after…

High Energy Physics - Theory · Physics 2014-11-18 C. Bervillier

A new weak Galerkin (WG) finite element method for solving the second-order elliptic problems on polygonal meshes by using polynomials of boundary continuity is introduced and analyzed. The WG method is utilizing weak functions and their…

Numerical Analysis · Mathematics 2015-09-30 Qilong Zhai , Xiu Ye , Ruishu Wang , Ran Zhang

This paper presents a detailed theoretical analysis of the three stochastic approximation proximal gradient algorithms proposed in our companion paper [49] to set regularization parameters by marginal maximum likelihood estimation. We prove…

Statistics Theory · Mathematics 2020-08-14 Valentin De Bortoli , Alain Durmus , Ana F. Vidal , Marcelo Pereyra

We consider minimizing a function consisting of a quadratic term and a proximable term which is possibly nonconvex and nonsmooth. This problem is also known as scaled proximal operator. Despite its simple form, existing methods suffer from…

Optimization and Control · Mathematics 2024-03-01 Yiming Zhou , Wei Dai

The Expectation-Maximization (EM) algorithm has been predominantly used to approximate the maximum likelihood estimation of the location-scale Gaussian mixtures. However, when the models are over-specified, namely, the chosen number of…

Machine Learning · Statistics 2022-05-24 Tongzheng Ren , Fuheng Cui , Sujay Sanghavi , Nhat Ho

We investigate the Polchinski ERG equation for d-dimensional O(N) scalar field theory. In the context of the non-perturbative derivative expansion we find families of regular solutions and establish their relation with the physical fixed…

High Energy Physics - Theory · Physics 2009-11-07 Yuri Kubyshin , Rui Neves , Robertus Potting

The paper deals with the numerical treatment of index-1 stochastic differential-algebraic equations (SDAEs) with nonlinear coefficients that satisfy the local Lipschitz and the Khasminskii conditions. The key challenge here is the presence…

Numerical Analysis · Mathematics 2026-04-16 Guy Tsafack , Antoine Tambue

We review the Exact Renormalization Group equations of Wegner and Houghton in an approximation which permits both numerical and analytical studies of nonperturbative renormalization flows. We obtain critical exponents numerically and with…

High Energy Physics - Theory · Physics 2009-09-25 Peter E. Haagensen , Yuri Kubyshin , José Ignacio Latorre , E. Moreno

We develop a simple non-perturbative approach to the calculation of a field theory effective potential that is based on the Wilson or exact renormalization group. Our approach follows Shepard et al's idea [Phys. Rev. D51, 7017 (1995)] of…

High Energy Physics - Theory · Physics 2022-07-05 Jose Gaite

This paper develops a functional-analytic framework for approximating the push-forward induced by an analytic map from finitely many samples. Instead of working directly with the map, we study the push-forward on the space of locally…

Numerical Analysis · Mathematics 2026-04-22 Isao Ishikawa